Approximate Networking

1. Approximate Networking H. T. Kung Harvard University Panel 1 on “What Are the Biggest Opportunities in Networking Problem?” NITRD Workshop on Complex Engineered NetworksWashington, DCSeptember 20-21, 2012

2. Wireless Networking Is ImportantBut ... • Peak bandwidth is physically limited for any given frequency band • Further exploitation in diversity (e.g., multipath and fine-grained beamforming) is getting increasingly difficult • Gap in meeting application demands is growing • Thus we need to find ways to fill the gap without violating Shannon's capacity theorem

3. Fortunately, There Are Opportunities • Many applications don’t need networks for exact packet delivery, for example: • Sensor data processing • Big data analysis • Probability distribution estimation • Image/vision object recognition and tracking • Machine learning • Biologically inspired systems • For these applications, approximate networking may be sufficient: • Deliver fraction of packets • Deliver approximate packets • Deliver combined packets

4. Advantages • We can use approximate network node hardware and protocols, and traffic-reducing networks • This allows efficient network implementation and robust network management • Moreover, this enables new security means, e.g., integrated encryption and compression using secret distortion distribution keys rather than compression followed by encryption • Theory in network coding and compressive sensing can be exploited

5. Summary • We have argued that approximate networking, especially for wireless networking, is a good opportunity for future networking